Our setting is close to generalized secretary problems [1]}, where the goal is to hire the best possible subset of candidates among a finite set of candidates arriving one at a time. A candidate's value is revealed upon arrival,
and the hiring decision must be taken immediately and cannot be changed afterwards. The connection between our work and this class of problems is detailed in Section REF . [2]} consider a bi-criteria secretary problem with multiple choices, where each criterion can be seen as a voter, the subset of choices as the elected committee, and their objective function as the multiwinner approval voting objective. We consider instead a multiplicity of voters, and various objectives corresponding to general Thiele rules in multiwinner voting. In the single secretary problem variant of [3]}, there are multiple independent attributes, which can be seen as voters in a single-winner election. In the context of search engines, [4]} aim to find a diverse set of items from an input stream, by maximizing a coverage function of multiple features. In our committee election framework, items can be seen as candidates and features as voters, yet their objective function is different from the committee scoring functions we consider, and proportional representation is not studied.
